For the first time, Australian researchers have reverse engineered the visual systems of hoverflies to develop drones capable of detecting other drones' acoustic signatures from almost four kilometers away. The research was published in the Journal of the Acoustical Society of America.
Autonomous systems experts from the University of South Australia (UniSA), Flinders University and defense company Midspar Systems say that trials using bio-inspired signal processing techniques show up to a 50 percent better detection rate than existing methods.
Hoverflies have a superior vision that can detect visual signs in complex landscapes. The researchers worked under the assumption that the same processes which allow small visual targets to be seen amongst visual clutter could be redeployed to extract low volume acoustic signatures from drones buried in noise.
By converting acoustic signals into two-dimensional 'images' (called spectrograms), researchers used the neural pathway of the hoverfly brain to suppress unrelated signals and noise, increasing the detection range for the sounds they wanted to detect.
Using their image-processing skills and sensing expertise, the researchers made this bio-inspired acoustic data breakthrough, which could help combat the growing global threat posed by IED-carrying drones, including in Ukraine.
“Bio-vision processing has been shown to greatly pick up clear and crisp acoustic signatures of drones, including very small and quiet ones, using an algorithm based on the hoverfly's visual system,” said UniSA Professor of Autonomous Systems and lead author Anthony Finn in a report.
“Unauthorized drones pose distinctive threats to airports, individuals and military bases. It is therefore becoming ever-more critical for us to be able to detect specific locations of drones at long distances, using techniques that can pick up even the weakest signals. Our trials using the hoverfly-based algorithms show we can now do this," noted Finn, who have high hopes for their new technique.
